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Professor Justin Cappos: The Extremes of Open-Source Code Security

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Manage episode 445659736 series 3533150
Indhold leveret af Matthew Mirman. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Matthew Mirman eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

What if you could significantly enhance your ability to spot confusing code patterns and bolster your software's resilience against potential attacks? Join us as we unpack the intricate world of misleading code patterns and their impact on software security. We start with an eye-opening study that identified a staggering 3.5 million confusing code patterns in popular projects. Discover how even seasoned programmers can be led astray by certain C code patterns, and learn why traditional methods of consulting experienced coders often fall short. Through detailed examples, we reveal how small "atoms" of confusion contribute to major errors in widely-used software like the Linux kernel and Apache.
Ever wondered how compiler fuzz testing can be a game-changer in identifying perplexing code? We'll walk you through the sophisticated techniques used in collecting and analyzing fuzzing tests from computer science programs. Learn about the role of tools like CodeQL and Clojure in pinpointing frequent yet confusing code patterns. We also delve into fascinating studies on programmer brain activity when confronting these challenges, and debate whether higher-level programming languages can ever be designed free of such confusing elements. By examining real-world cases, we illustrate how minor tweaks in code can lead to substantial improvements in software reliability.
Finally, we tackle the broader implications of software security and reproducibility. Gain insights into how signed attestations can safeguard the integrity of your software supply chain, preventing catastrophic attacks like SolarWinds. Explore the critical importance of reproducible builds, and understand why achieving bit-for-bit identical builds is a cornerstone of security. We'll also share practical tips for making your projects more reproducible, emphasizing the need for robust security measures and the ethical dimensions of our work in software development. Tune in for a compelling discussion that intertwines technical depth with actionable insights, aimed at strengthening both your code and your security posture.

Accelerometer Podcast
Accelerometer Youtube
Anarchy
Anarchy Discord
Anarchy LLM-VM
Anarchy Twitter
Anarchy LinkedIn
Matthew Mirman LinkedIn

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Kapitler

1. Identifying Confusing Code Patterns in Programming (00:00:00)

2. Uncovering Confusing Code Patterns in Programming (00:04:43)

3. Quantifying Confusing Code Patterns in Programming (00:14:28)

4. Ensuring Software Security Through Attestation (00:21:39)

5. Achieving Reproducibility in Software (00:31:13)

6. Promoting Software Security Through Advocacy (00:37:52)

22 episoder

Artwork
iconDel
 
Manage episode 445659736 series 3533150
Indhold leveret af Matthew Mirman. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Matthew Mirman eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

What if you could significantly enhance your ability to spot confusing code patterns and bolster your software's resilience against potential attacks? Join us as we unpack the intricate world of misleading code patterns and their impact on software security. We start with an eye-opening study that identified a staggering 3.5 million confusing code patterns in popular projects. Discover how even seasoned programmers can be led astray by certain C code patterns, and learn why traditional methods of consulting experienced coders often fall short. Through detailed examples, we reveal how small "atoms" of confusion contribute to major errors in widely-used software like the Linux kernel and Apache.
Ever wondered how compiler fuzz testing can be a game-changer in identifying perplexing code? We'll walk you through the sophisticated techniques used in collecting and analyzing fuzzing tests from computer science programs. Learn about the role of tools like CodeQL and Clojure in pinpointing frequent yet confusing code patterns. We also delve into fascinating studies on programmer brain activity when confronting these challenges, and debate whether higher-level programming languages can ever be designed free of such confusing elements. By examining real-world cases, we illustrate how minor tweaks in code can lead to substantial improvements in software reliability.
Finally, we tackle the broader implications of software security and reproducibility. Gain insights into how signed attestations can safeguard the integrity of your software supply chain, preventing catastrophic attacks like SolarWinds. Explore the critical importance of reproducible builds, and understand why achieving bit-for-bit identical builds is a cornerstone of security. We'll also share practical tips for making your projects more reproducible, emphasizing the need for robust security measures and the ethical dimensions of our work in software development. Tune in for a compelling discussion that intertwines technical depth with actionable insights, aimed at strengthening both your code and your security posture.

Accelerometer Podcast
Accelerometer Youtube
Anarchy
Anarchy Discord
Anarchy LLM-VM
Anarchy Twitter
Anarchy LinkedIn
Matthew Mirman LinkedIn

  continue reading

Kapitler

1. Identifying Confusing Code Patterns in Programming (00:00:00)

2. Uncovering Confusing Code Patterns in Programming (00:04:43)

3. Quantifying Confusing Code Patterns in Programming (00:14:28)

4. Ensuring Software Security Through Attestation (00:21:39)

5. Achieving Reproducibility in Software (00:31:13)

6. Promoting Software Security Through Advocacy (00:37:52)

22 episoder

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